PhD defense Yatong Wang: ‘Data-driven discovery of 2D materials as photocatalysts for water splitting’

DIFFER researcher Yatong Wang will defend his PhD thesis titled: ‘Data-driven discovery of 2D materials as photocatalysts for water splitting’.

Summary: Green hydrogen (H2), produced sustainably, presents a promising clean energy alternative to traditional fossil fuels, especially as the shift towards renewable energy accelerates. In this context, solar water splitting for H2 production has gained significant interest in recent years. However, the efficiency of this method is substantially impeded by the performance of photocatalysts. Two-dimensional (2D) materials are emerging as potential photocatalysts due to their large specific surface area, abundant active sites, effective sunlight absorption, and short carrier migration distance. Yet, the discovery of 2D materials that fulfill essential photocatalyst criteria, such as having moderate band gaps to maximize solar energy absorption and appropriate band edge positions aligning with the water redox potentials, remains challenging. With significant growth in computing power and available computational data, the field of material discovery has evolved into a data-driven era, characterized by big-data
and advanced machine-learning (ML) algorithms. Utilizing ML-predicted properties, one can conduct an application-focused preliminary screening of a wide range of materials, followed by more precise computations, such as density functional theory (DFT), to further investigate the selected materials. In this thesis, we adopt a data-driven strategy to effectively identify 2D materials as potential photocatalysts for solar water splitting.

TU/e Atlas 0.710
Yatong Wang

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